Hello, I have y (dependent variable) and x (independent variable) data and want to develop a logistic model in the form of y = ymax/(1+exp(b-k*x). I want to optimize the solution to get b and k value by writing a function and solving them using 'fminunc'.
The values are like: ydata = [1.5 1.8 2.1 2.5 2.65 2.75] with xdata = [1 3 5 7 10 20], ymax = max(ydata). I wrote following code: function f = glass(x,xdata, ydata) f = (2.06/(1+exp(x(1)-x(2)*xdata)))- ydata;
in command window: ydata = [1.5 1.8 2.1 2.5 2.65 2.75]; xdata = [1 3 5 7 10 20]; x0 = [0.5; 0.5]; F = @(x)glass(x,xdata, ydata); [x,fval] = fminunc(F,x0) but it fails every time and says too many input input argument. Also want to mention quasi-newton algorithm to optimize it. How could I solve this problem?
Any help is appreciating.
